• Journal of Korea Water Resources Association
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• v.48 no.4
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• pp.257-268
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• 2015

The objective of this study is to assess the dual-polarization radar for flood forecasting. First, radar rainfall has temporal and spatial errors, so estimated radar rainfall was compared with ground observation rainfall to assess accuracy improvement, especially, considering the radar range of observation and increase of the rainfall intensity. The results of this study showed that the error for estimated dual-polarization radar rainfall was less than single-polarization radar rainfall. And in this study, dual-polarization radar rainfall for flood forecasting was assessed using MAP (Mean Areal Precipitation) and SURR (Sejong University Rainfall Runoff) model in Namkang dam watershed. The results of MAP are more accurate using dual-polarization radar. And the results of runoff using dual-polarization radar rainfall showed that peak flow error was reduced approximately 12~63%, runoff volumes error was reduced by approximately 30~42%, and also the root mean square error decreased compared to the result of runoff using single-polarization radar rainfall. The results revealed that dual-polarization radar will contribute to improving the accuracy of the flood forecasting.

• Korean Journal of Agricultural and Forest Meteorology
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• v.13 no.2
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• pp.87-92
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• 2011

In order to better understand the role of litter layer on hydrological cycle in forest, we estimated the interception storage capacity of the litter layer at Gwangneung deciduous forest. We first made a thickness map of the litter layer at the study site based on field survey and then collected representative litter samples for the laboratory experiment. We constructed a measurement device consisting of sample tray, drain collector, tipping bucket, and a data logger. Using this device, we examined the relationship between the interception storage capacity ($C_i$) and the thickness (d) of the litter layer. For the range of d from 25 to 100 mm, there was a simple linear relationship between $C_i$ and d, which changed with the intensity of the simulated rain. The results were extrapolated to d smaller than 25 mm by considering that no interception occurs without litter layer. Overall, $C_i$ increased rapidly when d was low (< 25 mm) but the rate of increase decreased as d increased due to clumping. With an average thickness of 59 mm, the estimated $C_i$ at the site was 0.94 (${\pm}0.39$) mm. Such an interception storage capacity of the litter layer is comparable to that of the forest canopy, suggesting that the litter layer can play an important role in the forest water cycle.

• Korean Journal of Remote Sensing
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• v.39 no.1
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• pp.47-63
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• 2023

Unmanned aerial vehicle (UAV) and sensor technologies are rapidly developing and being usefully utilized for spatial information-based agricultural management and smart agriculture. Until now, there have been many difficulties in obtaining production information in a timely manner for large-scale agriculture on reclaimed land. However, smart agriculture that utilizes sensors, information technology, and UAV technology and can efficiently manage a large amount of farmland with a small number of people is expected to become more common in the near future. In this study, we evaluated the productivity of forage maize grown on reclaimed land using UAV and sensor-based technologies. This study compared the plant height, vegetation cover ratio, fresh biomass, and dry biomass of maize grown on general farmland and reclaimed land in South Korea. A biomass model was constructed based on plant height, cover ratio, and volume-based biomass using UAV-based images and Farm-Map, and related estimates were obtained. The fresh biomass was estimated with a very precise model (R² =0.97, root mean square error [RMSE]=3.18 t/ha, normalized RMSE [nRMSE]=8.08%). The estimated dry biomass had a coefficient of determination of 0.86, an RMSE of 1.51 t/ha, and an nRMSE of 12.61%. The average plant height distribution for each field lot was about 0.91 m for reclaimed land and about 1.89 m for general farmland, which was analyzed to be a difference of about 48%. The average proportion of the maize fraction in each field lot was approximately 65% in reclaimed land and 94% in general farmland, showing a difference of about 29%. The average fresh biomass of each reclaimed land field lot was 10 t/ha, which was about 36% lower than that of general farmland (28.1 t/ha). The average dry biomass in each field lot was about 4.22 t/ha in reclaimed land and about 8 t/ha in general farmland, with the reclaimed land having approximately 53% of the dry biomass of the general farmland. Based on these results, UAV and sensor-based images confirmed that it is possible to accurately analyze agricultural information and crop growth conditions in a large area. It is expected that the technology and methods used in this study will be useful for implementing field-smart agriculture in large reclaimed areas.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.4
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• pp.1335-1342
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• 2014

Shallow water depths were estimated using Compact Airborne Spectrographic Imager (CASI)-1500 and mapped to analyze the bottom bathymetry changes due to the rip currents in Haeundae beach, South Korea for the first time. The depths were estimated empirically using the maximum reflectances from 420nm to 597nm wavelength of CASI and 47 in situ water depth measurements, which were compared with ground-truth bathymetry measurements. The comparisons showed that the RMSE was 1.1m with a correlation coefficient of 0.76. In addition, CASI imagery showed remarkably detailed bottom features, especially those resulting from the rip currents within the beach. Two different channels carved by the rip current were analyzed and characterized with respect to the width and slope compared to surrounding regions. While the west side of the channel showed a wide and gentle slope, the east side of the channel showed a narrow and steep slope. The estimated bathymetry map revealed that the uneven offshore bottom features were related to the transport and accumulation of sediments by the rip current, which reaches hundreds of meters offshore. Accordingly, the accumulated sediments were estimated by adding topography changes compared to the depths of the non-rip current regions. The sediments were accumulated in off channels as much as almost twice the amount of annual sand supplements along the Haeundae beach.

• Journal of Korean Society of Forest Science
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• v.101 no.3
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• pp.509-516
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• 2012

In this research, it was intended to examine the vulnerability of Pinus rigida to climate changes, a major planting species in Korea. For this purpose, the distribution of Pinus rigida and its changes caused by climate changes were estimated based on the 'A1B' climate change scenario suggested by IPCC. Current distribution of Pinus rigida was analyzed by using the $4^{th}$Forest Type Map and its potential distribution in the recent year (2000), the near future (2050) and the further future (2100) were estimated by analyzing the optimized ranges of three climate indices - warmth index(WI), minimum temperature index of the coldest month (MTCI) and precipitation effectiveness index(PEI). The results showed that the estimated potential distribution of Pinus rigida declines to 56% in the near future(2050) and 15% in the further future (2100). This significant decline was found in most provinces in Korea. However, in Kangwon province where the average elevation is higher than other provinces, the area of potential distribution of Pinus rigida increases in the near future and the further future. Also the result indicated that the potential distribution of Pinus rigida migrates to higher elevation. The potential distributions estimated in this research have relatively high accuracy with consideration of classification accuracy (44.75%) and prediction probability (62.56%).

• Korean Chemical Engineering Research
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• v.56 no.6
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• pp.841-855
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• 2018

The purpose of this study is to estimate the available potential heat source for heat pump in the district heating supply area in the city. Unused energy potentials were estimated and integrated based on open source based data. In particular, geographical spatial analysis of recoverable heat energy density and heat demand in the heat source area of large retailers and public sauna facilities in the DH network located in the southern part of the metropolitan area (Pyeongtaek-si) was conducted. As a result of the study, the DH network area had a total potential energy of 1,741.7 toe/year for the two heat sources of large retailers and public saunas. It is estimated that 1,006.9 toe/year, which is 57.8% of the total, can be linked to the district heating. The large retailers showed a positive correlation with the floor area and energy use of 0.4937. The recoverable energy intensity was estimated to be $0.0017toe/m^2$ per unit area and $0.0069tCO_2/m^2$ for greenhouse gas emissions. In addition, public saunas were analyzed by comparing the empirical case with the theoretical calculation, and it was estimated that energy conservation estimate of 80% was $0.0315toe/m^2$ per bath area and $0.1183tCO_2/m^2$ for greenhouse gas emissions. The total potential energy amount of this area was positively correlated with the heat demand of apartment house by administrative district, and it was confirmed that it had a relatively high potential energy especially in traffic and commercial center.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.4
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• pp.69-85
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• 2014

Carbon stocks of NFI plots can be accurately estimated using field survey information. However, an accurate estimation of carbon stocks in other unsurveyed sites is very difficult. In order to fill this gap, various spatial information can be used as an ancillary data. In South Korea, there is the 1:5,000 forest type map that was produced by digital air-photo interpretation and field survey. Because this map contains very detailed forest information, it can be used as the high-quality spatial data for estimating carbon stocks. In this study, we compared three upscaling methods based on the 1:5,000 forest type map and 5th national forest inventory data. Map algebra(method 1), RK(Regression Kriging)(method 2), and GWR(Geographically Weighted Regression)(method 3) were applied to estimate forest carbon stock in Chungcheong-nam Do and Daejeon metropolitan city. The range of carbon stocks from method 2(1.39~138.80 tonC/ha) and method 3(1.28~149.98 tonC/ha) were more similar to that of previous method(1.56~156.40 tonC/ha) than that of method 1(0.00~93.37 tonC/ha). This result shows that RK and GWR considering spatial autocorrelation can show spatial heterogeneity of carbon stocks. We carried out paired t-test for carbon stock data using 186 sample points to assess estimation accuracy. As a result, the average carbon stocks of method 2 and field survey method were not significantly different at p=0.05 using paired t-test. And the result of method 2 showed the lowest RMSE. Therefore regression kriging method is useful to consider spatial variations of carbon stocks distribution in rugged terrain and complex forest stand.

• Journal of Korean Society of Transportation
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• v.33 no.3
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• pp.294-303
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• 2015

This paper describes a method that can be used for estimating future carbon emissions and environmental effects. To forecast future land use and transportation changes under various low carbon policies, a DELTA and OmniTRANS combination (a land use-transport integrated model) was applied. Appropriate emission estimation methods and dispersion models were selected and applied in the method. It was designed that the estimated emissions from land use and transportation activity as well as the estimated concentrations of air pollutants and comprehensive air quality index (CAI) are presented on a GIS-based map. The prototype was developed for the city of Suwon and the outcome examples were presented in this paper; it demonstrates what kinds of analysis results are presented in this method. It is expected that the developed method will be very useful for decision makers who want to know the effect of environmental policies in cities.

• Journal of Biosystems Engineering
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• v.34 no.5
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• pp.382-389
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• 2009

An in-situ probe-based spectrophotometer has been developed. This system used two spectrometers to measure soil reflectance spectra from 450 nm to 2200 nm. It collects soil electrical conductivity (EC) and insertion force measurements in addition to the optical data. Six fields in Kansas were mapped with the VIS-NIR (visible-near infrared) probe module and sampled for calibration and validation. Results showed that VIS-NIR correlated well with carbon in all six fields, with RPD (the ratio of standard deviation to root mean square error of prediction) of 1.8 or better, RMSE of 0.14 to 0.22%, and $R^2$ of 0.69 to 0.89. From the investigation of carbon variability within the soil profile and by tillage practice, the 0-5 cm depth in a no-till field contained significantly higher levels of carbon than any other locations. Using the selected calibration model with the soil NIR probe data, a soil profile map of estimated carbon was produced, and it was found that estimated carbon values are highly correlated to the lab values. The array of sensors (VIS-NIR, electrical conductivity, insertion force) used in the probe allowed estimating bulk density, and three of the six fields were satisfactory. The VIS-NIR probe also showed the obtained spectra data were well correlated with nitrogen for all fields with RPD scores of 1.84 or better and coefficient of determination ($R^2$) of 0.7 or higher.

• Journal of Korean Society on Water Environment
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• v.28 no.1
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• pp.137-147
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• 2012

Land surface temperature in ecohydrology is a variable that links surface structure to soil processes and yet its spatial prediction across landscapes with variable surface structure is poorly understood. And there are an insufficient number of soil temperature monitoring stations. In this study, a grid-based land surface temperature prediction model is proposed. Target sites are Andong and Namgang dam region. The proposed model is run in the following way. At first, geo-referenced site specific air temperatures are estimated using a kriging technique from data collected from 60 point weather stations. Then surface soil temperature is computed from the estimated geo-referenced site-specific air temperature and normalized difference vegetation index. After the model is calibrated with data collected from observed remote-sensed soil temperature, a soil temperature map is prepared based on the predictions of the model for each geo-referenced site. The daily and monthly simulated soil temperature shows that the proposed model is useful for reproducing observed soil temperature. Soil temperatures at 30 and 50 cm of soil depth are also well simulated.